Exploratory Analysis of Spatial and Temporal Data - Info and Reading Options
A Systematic Approach
By Natalia Andrienko and Gennady Andrienko
"Exploratory Analysis of Spatial and Temporal Data" is published by Springer in December 21, 2005, it has 703 pages and the language of the book is English.
“Exploratory Analysis of Spatial and Temporal Data” Metadata:
- Title: ➤ Exploratory Analysis of Spatial and Temporal Data
- Authors: Natalia AndrienkoGennady Andrienko
- Language: English
- Number of Pages: 703
- Publisher: Springer
- Publish Date: December 21, 2005
“Exploratory Analysis of Spatial and Temporal Data” Subjects and Themes:
- Subjects: ➤ Spatial analysis (Statistics) - Multivariate analysis - Temporal databases - Information storage and retrieval systems - Analyse multivariée - Analyse spatiale (Statistique) - Bases de données spatio-temporelles - Computer science - Geographical information systems - Computer Applications - Geographical Information Systems/Cartography - Computer Applications in Geosciences - Information Storage and Retrieval
Edition Specifications:
- Format: Hardcover
- Weight: 2.8 pounds
- Dimensions: 9.5 x 6.3 x 1.7 inches
Edition Identifiers:
- The Open Library ID: OL9055582M - OL18725427W
- Online Computer Library Center (OCLC) ID: 64571808
- Library of Congress Control Number (LCCN): 2005936053
- ISBN-13: 9783540259947
- ISBN-10: 3540259945
- All ISBNs: 3540259945 - 9783540259947
AI-generated Review of “Exploratory Analysis of Spatial and Temporal Data”:
"Exploratory Analysis of Spatial and Temporal Data" Description:
The Open Library:
Exploratory data analysis (EDA) is about detecting and describing patterns, trends, and relations in data, motivated by certain purposes of investigation. As something relevant is detected in data, new questions arise, causing specific parts to be viewed in more detail. So EDA has a significant appeal: it involves hypothesis generation rather than mere hypothesis testing. The authors describe in detail and systemize approaches, techniques, and methods for exploring spatial and temporal data in particular. They start by developing a general view of data structures and characteristics and then build on top of this a general task typology, distinguishing between elementary and synoptic tasks. This typology is then applied to the description of existing approaches and technologies, resulting not just in recommendations for choosing methods but in a set of generic procedures for data exploration. Professionals practicing analysis will profit from tested solutions – illustrated in many examples – for reuse in the catalogue of techniques presented. Students and researchers will appreciate the detailed description and classification of exploration techniques, which are not limited to spatial data only. In addition, the general principles and approaches described will be useful for designers of new methods for EDA.
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